Business Intelligence Analyst - Digital Experience

Savills
Peterborough
3 weeks ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Lead Business Intelligence Analyst

Overview

We are looking for a Business Intelligence Analyst to join the Global Occupier Services team in our Peterborough office.

Role and responsibilities

The Business Intelligence Analyst will be responsible for the creation and management of dashboards and business reporting and tracking solutions.

This is a pivotal role, so ideally the candidate should be used to working in a fast-paced environment, have excellent attention to detail and be willing to come forward with innovative ideas reflecting technical change in our industry. The candidate must be very organised, be able to take initiative. A self-motivated individual, they will also be able to demonstrate reliability, flexibility and initiative.

You will be working under our growing Business Intelligence Development team, and within the wider context of the Global Occupier Services Team.

Please note this role is fully office based in our Peterborough office.

Click here to download the full job specification. Please ensure you read this before applying.

What we offer you
  • Career and Professional Development
  • 25-30 Days Annual Leave, depending on grade
  • Life Assurance
  • Private Medical Scheme
  • Virtual GP
  • Global Mobility Scheme
  • Rewards Platform
  • Company Pension Scheme
  • Enhanced Incremental Annual Leave
Team Overview

Global Occupier Services (GOS) is a team that primarily deals with clients who occupy, typically via leases, large amounts of space to conduct business operations. The team consists of account managers and strategic consultants who provide a single point of contact for our clients, approach them with optimisation strategy and manage large projects and change within their portfolios. The Digital Experience team sits within GOS and specialises in analysing, curating and visualising client data along with Savills internal data to provide a full reporting suite to clients, as well as taking on ad hoc data driven projects. The Digital Experience team is looking for an inquisitive, proficient analyst who can demonstrate problem solving ability and a flair for creating interesting and engaging visuals for reporting and presentation purposes.

This role does not meet the salary criteria for skilled worker visa sponsorship (check exemptions).

To be eligible to apply for this role you must hold your own right to work in the UK. Please check here that you\'re able to make a new application to us now. Our employees act with honesty and integrity so we expect the same from you. We take any attempts to circumvent this policy very seriously.

Recruitment agencies

Savills only pay agency fees where we have a signed agreement in place and that agency has been previously contacted and directed by a member of our recruitment team. We do not pay agency fees when speculative and unsolicited CVs are submitted to Savills or any of our employees other than via our careers website and through our recruitment process. If this is not adhered to, agency fees will not be paid.

Submission of any unsolicited CVs or proposals to Savills will be deemed evidence of full and unlimited acceptance of this approach.

Over 42,000 people work for us in more than 70 countries all over the world. This breadth of global coverage, combined with specialist services and market insight, means we\'ll always have an expert who is local to you.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.